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Oil pollution and water deficit are threat to the environment and can impose serious problems in crop yield and productivity. Early detection and discrimination between these stress agents are important to facilitate timely delivery of remedial measures. Remote sensing technology has this potential but there is poor understanding about the ability of the combined spectral and thermal information for early detection and discrimination between oil and water deficit-induced stress in plants. In order to understand this, in a glasshouse, pot grown maize was treated with oil, water deficit and combined oil and water deficit. Thereafter, leaf thermal, spectral and physiological measurements were taken every 2 to 3 days to monitor the development of stress responses. Our result showed that stress caused by oil pollution can be detected spectrally before visual stress symptoms are observed in maize but it was a poor indicator of water deficit stress. On the contrary, leaf absolute temperature can indicate water deficit stress prior to visual stress symptoms, although it may be difficult to discriminate between oil and water deficit stress using this measure. Based on our findings, we conclude that the combination of hyperspectral and thermal remote sensing has potential in the early detection and discrimination between oil and water deficit stress in maize. Keywords - Oil pollution, Spectral reflectance, thermography, Water deficit, Maize.

Detection and discrimination of oil and water deficit-induced stress in maize (Zea mays L.) using spectral and thermal responses